Hervé Lombaert: Graph Convolutions - Examples on brain surfaces

Hervé Lombaert is a Professor at ETS Montreal, Canada, where he holds a Canada Research Chair in Shape Analysis in Medical Imaging. His research focuses on the statistics and analysis of shapes in the context of machine learning and medical imaging. His work on graph analysis has impacted the performance of several applications in medical imaging, from the early image segmentation techniques with graph cuts, to recent surface analysis with spectral graph theory and graph convolutional networks. He had the chance to work in multiple centers, including Microsoft Research (Cambridge, UK), Siemens Corporate Research (Princeton, NJ), Inria Sophia-Antipolis (France), McGill University (Canada), and the University of Montreal (Canada). His research has also received several awards, including the Erbsmann Prize in Medical Imaging.

More at [https://profs.etsmtl.ca/hlombaert]
Timestamps:
0:00 Setting up zoom
0:45 Introduction
4:55 Geometry and machine learning
8:28 Neighborhoods on surfaces
11:30 Convolutions on surfaces
12:31 Spectral coordinates
25:07 Learning on surfaces
27:44 Geometric deep learning
35:53 Challenges in medical imaging
41:03 Localized graph convolutions
50:39 Q & A

Видео Hervé Lombaert: Graph Convolutions - Examples on brain surfaces канала Machine learning and image analysis